Compare ratings with stats

Stats bring additional performance context into a calibration. Alongside manager review ratings, you can use connected data—such as quota attainment or project delivery—as a grid axis or table column. Stats are evidence for discussion, not editable review answers. A facilitator can change a rating in response to the committee’s decision, but cannot change the underlying stat from the calibration.

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How stats work in calibration

Windmill makes eligible stats available for reviewees when the connected data falls within the performance review cycle’s review period. You can use a stat in two places:

• Grid — Select a stat as either axis to compare it with a rating or another stat.
• Table — Add stats as columns for a compact comparison across the roster.

On the grid, Windmill groups numeric stat values into five peer-relative bands based on the population mean and standard deviation of reviewees who have data in that calibration. This makes it easier to see relative position without changing the source data. If fewer than five reviewees have a value, or every value is the same, Windmill shows a single band because it cannot create meaningful peer-relative groups.

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Choose useful stats

The strongest stats have a clear connection to the rating being discussed and are reasonably comparable across the selected group. Useful examples include:

• Sales: quota attainment, closed revenue, or pipeline created
• Customer Success: retention, expansion, or portfolio health
• Support: cases resolved, customer satisfaction, or response time
• Engineering: project delivery or relevant quality and reliability measures
• Recruiting: hires completed or time to fill

Avoid using activity volume as a shortcut for performance. A high count may reflect role design, assignment mix, or data availability rather than greater impact.

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Build a rating-versus-stat grid

Because the stat axis is read-only, facilitators can drag reviewees only along the rating axis.

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Example use cases

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Find a rating that needs more context

A salesperson has high quota attainment but a lower overall rating. The committee opens the packet to learn whether the rating reflects collaboration, forecast quality, or another expectation not captured by quota.

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Compare managers’ standards

Table view shows rating and outcome data across several teams. One manager’s ratings are consistently higher for similar results. The committee reviews packets to determine whether the difference reflects context or inconsistent use of the rubric.

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Avoid penalizing a strong team

A high-performing employee is rated lower than peers on a very strong team. Comparing the broader cohort and opening the evidence helps the committee assess the person against role expectations rather than only their immediate teammates.

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Interpret stats responsibly

• Check whether the stat covers the full review period.
• Compare people with similar responsibilities and opportunity.
• Consider data quality and missing values.
• Use multiple sources of evidence before changing a rating.
• Never treat a stat band as an automatic rating recommendation.

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FAQs